EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

• URL: http://arxiv.org/abs/2603.11703v1
• Date: Thu, 12 Mar 2026 09:10:36 GMT
• Title: EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering
• Abstract summary: EvoFlows is a variable-length sequence-to-sequence protein modeling approach.<n>Unlike autoregressive and masked language models, EvoFlows perform a limited, controllable number of insertions, deletions, and substitutions on a template protein sequence.
• Score: 2.446672595462589
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce EvoFlows, a variable-length sequence-to-sequence protein modeling approach uniquely suited to protein engineering. Unlike autoregressive and masked language models, EvoFlows perform a limited, controllable number of insertions, deletions, and substitutions on a template protein sequence. In other words, EvoFlows predict not only _which_ mutation to perform, but also _where_ it should occur. Our approach leverages edit flows to learn mutational trajectories between evolutionarily-related protein sequences, simultaneously modeling distributions of related natural proteins and the mutational paths connecting them. Through extensive _in silico_ evaluation on diverse protein communities from UNIREF and OAS, we demonstrate that EvoFlows capture protein sequence distributions with a quality comparable to leading masked language models commonly used in protein engineering, while showing improved ability to generate non-trivial yet natural-like mutants from a given template protein.

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